Bellabeat Case Study
Qanitah Nizam
2022-10-28
Install & Load Packages
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## date, intersect, setdiff, unionImporting Data sets
## Rows: 940 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): ActivityDate
## dbl (14): Id, TotalSteps, TotalDistance, TrackerDistance, LoggedActivitiesDi...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Examining Data
## [1] 940 15## [1] 413 5## [1] 67 8Checking for Null & Duplicate values
## [1] 0## [1] 0## [1] 65## Id Date WeightKg WeightPounds Fat
## 0 0 0 0 65
## BMI IsManualReport LogId
## 0 0 0## Id Date WeightKg WeightPounds BMI IsManualReport
## 1 1503960366 5/2/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE
## 2 1503960366 5/3/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE
## 3 1927972279 4/13/2016 1:08:52 AM 133.5 294.3171 47.54 FALSE
## 4 2873212765 4/21/2016 11:59:59 PM 56.7 125.0021 21.45 TRUE
## 5 2873212765 5/12/2016 11:59:59 PM 57.3 126.3249 21.69 TRUE
## 6 4319703577 4/17/2016 11:59:59 PM 72.4 159.6147 27.45 TRUE
## LogId
## 1 1.462234e+12
## 2 1.462320e+12
## 3 1.460510e+12
## 4 1.461283e+12
## 5 1.463098e+12
## 6 1.460938e+12## [1] 0## [1] 3## [1] 0Extracting days from date
## tibble [940 × 16] (S3: tbl_df/tbl/data.frame)
## $ Id : num [1:940] 1.5e+09 1.5e+09 1.5e+09 1.5e+09 1.5e+09 ...
## $ ActivityDate : chr [1:940] "4/12/2016" "4/13/2016" "4/14/2016" "4/15/2016" ...
## $ TotalSteps : num [1:940] 13162 10735 10460 9762 12669 ...
## $ TotalDistance : num [1:940] 8.5 6.97 6.74 6.28 8.16 ...
## $ TrackerDistance : num [1:940] 8.5 6.97 6.74 6.28 8.16 ...
## $ LoggedActivitiesDistance: num [1:940] 0 0 0 0 0 0 0 0 0 0 ...
## $ VeryActiveDistance : num [1:940] 1.88 1.57 2.44 2.14 2.71 ...
## $ ModeratelyActiveDistance: num [1:940] 0.55 0.69 0.4 1.26 0.41 ...
## $ LightActiveDistance : num [1:940] 6.06 4.71 3.91 2.83 5.04 ...
## $ SedentaryActiveDistance : num [1:940] 0 0 0 0 0 0 0 0 0 0 ...
## $ VeryActiveMinutes : num [1:940] 25 21 30 29 36 38 42 50 28 19 ...
## $ FairlyActiveMinutes : num [1:940] 13 19 11 34 10 20 16 31 12 8 ...
## $ LightlyActiveMinutes : num [1:940] 328 217 181 209 221 164 233 264 205 211 ...
## $ SedentaryMinutes : num [1:940] 728 776 1218 726 773 ...
## $ Calories : num [1:940] 1985 1797 1776 1745 1863 ...
## $ Weekday : chr [1:940] "Tuesday" "Wednesday" "Thursday" "Friday" ...Unique users
## [1] 33## [1] 24## [1] 8Manual Recordings
## # A tibble: 5 × 2
## Id `Manual Weight Report`
## <dbl> <int>
## 1 1503960366 2
## 2 2873212765 2
## 3 4319703577 2
## 4 4558609924 5
## 5 6962181067 30Merging Data Sets
## Id ActivityDate TotalSteps TotalDistance TrackerDistance
## 13 1503960366 5/9/2016 12022 7.72 7.72
## 14 1503960366 5/9/2016 12022 7.72 7.72
## 15 1503960366 5/9/2016 12022 7.72 7.72
## 16 1503960366 5/9/2016 12022 7.72 7.72
## 17 1503960366 5/9/2016 12022 7.72 7.72
## 18 1503960366 5/9/2016 12022 7.72 7.72
## LoggedActivitiesDistance VeryActiveDistance ModeratelyActiveDistance
## 13 0 3.45 0.53
## 14 0 3.45 0.53
## 15 0 3.45 0.53
## 16 0 3.45 0.53
## 17 0 3.45 0.53
## 18 0 3.45 0.53
## LightActiveDistance SedentaryActiveDistance VeryActiveMinutes
## 13 3.74 0 46
## 14 3.74 0 46
## 15 3.74 0 46
## 16 3.74 0 46
## 17 3.74 0 46
## 18 3.74 0 46
## FairlyActiveMinutes LightlyActiveMinutes SedentaryMinutes Calories Weekday
## 13 11 206 835 1819 Monday
## 14 11 206 835 1819 Monday
## 15 11 206 835 1819 Monday
## 16 11 206 835 1819 Monday
## 17 11 206 835 1819 Monday
## 18 11 206 835 1819 Monday
## SleepDay TotalSleepRecords TotalMinutesAsleep TotalTimeInBed
## 13 4/23/2016 12:00:00 AM 1 361 384
## 14 4/23/2016 12:00:00 AM 1 361 384
## 15 4/24/2016 12:00:00 AM 1 430 449
## 16 4/24/2016 12:00:00 AM 1 430 449
## 17 4/25/2016 12:00:00 AM 1 277 323
## 18 4/25/2016 12:00:00 AM 1 277 323
## Date WeightKg WeightPounds BMI IsManualReport LogId
## 13 5/3/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE 1.462320e+12
## 14 5/2/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE 1.462234e+12
## 15 5/3/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE 1.462320e+12
## 16 5/2/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE 1.462234e+12
## 17 5/3/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE 1.462320e+12
## 18 5/2/2016 11:59:59 PM 52.6 115.9631 22.65 TRUE 1.462234e+12Data Recorded during the week
From the bar graph the data is greatest from Tuesday to Thursday. Monday and Friday are both weekdays, why isn’t the data recordings as much as the other weekdays?
Total Minutes Asleep during the week
Summary
## Weekday TotalSteps TotalDistance VeryActiveMinutes
## Monday :4352 Min. : 0 Min. : 0.00 Min. : 0.00
## Tuesday :5440 1st Qu.: 5908 1st Qu.: 3.91 1st Qu.: 0.00
## Wednesday:5440 Median :10320 Median : 6.82 Median : 18.00
## Thursday :5414 Mean : 9657 Mean : 6.49 Mean : 23.73
## Friday :4352 3rd Qu.:12207 3rd Qu.: 8.35 3rd Qu.: 38.00
## Saturday :4352 Max. :20031 Max. :13.24 Max. :210.00
## Sunday :4352
## FairlyActiveMinutes LightlyActiveMinutes SedentaryMinutes Calories
## Min. : 0.00 Min. : 0.0 Min. : 0.0 Min. : 0
## 1st Qu.: 4.00 1st Qu.:199.0 1st Qu.: 634.0 1st Qu.:1850
## Median :15.00 Median :243.0 Median : 683.0 Median :2039
## Mean :18.32 Mean :241.5 Mean : 689.4 Mean :2011
## 3rd Qu.:33.00 3rd Qu.:295.0 3rd Qu.: 731.0 3rd Qu.:2173
## Max. :74.00 Max. :432.0 Max. :1440.0 Max. :4552
##
## TotalMinutesAsleep TotalTimeInBed WeightPounds
## Min. : 59.0 Min. : 65.0 Min. :116.0
## 1st Qu.:411.0 1st Qu.:424.0 1st Qu.:134.9
## Median :442.0 Median :457.0 Median :135.6
## Mean :437.5 Mean :456.3 Mean :138.6
## 3rd Qu.:476.0 3rd Qu.:497.0 3rd Qu.:136.5
## Max. :750.0 Max. :775.0 Max. :294.3
## Active Minutes Analysis
Percentage of active minutes in the four categories: very active, fairly active, lightly active and sedentary. From the pie chart, we can see that most users spent 81.3% of their daily activity in sedentary minutes and only 1.74% in very active minutes.
A/c to American Health Association daily goal of fairly_active_minutes = 21.4 or 10.7 minutes of Very_Active_Minutes.
## # A tibble: 6 × 2
## # Groups: Id [6]
## Id n
## <dbl> <int>
## 1 1503960366 30
## 2 1624580081 6
## 3 1644430081 16
## 4 1927972279 2
## 5 2022484408 28
## 6 2320127002 2Noticeable day
The bar graph shows that there is a jump on Saturday user spent LESS time in sedentary minutes and take MORE steps. Users are out and about on Saturday.
Hourly Steps
From 5PM to 7PM the users take the most steps.
## Id ActivityHour StepTotal Hour
## 1 1503960366 2016-04-12 00:00:00 373 00
## 2 1503960366 2016-04-12 01:00:00 160 01
## 3 1503960366 2016-04-12 02:00:00 151 02
## 4 1503960366 2016-04-12 03:00:00 0 03
## 5 1503960366 2016-04-12 04:00:00 0 04
## 6 1503960366 2016-04-12 05:00:00 0 05
Weekly steps
Tuesday and Saturdays the users take the most steps.
Total Steps Vs. Calories
Here we see that some users who are sedentary, take minimal steps, but still able to burn over 1500 to 2500 calories compare to users who are more active, take more steps, but still burn similar calories.
## `geom_smooth()` using formula 'y ~ x'
## Steps Vs. Active Minutes
Comparing the four active levels to the total steps, we see most data is concentrated on users who take about 5000 to 15000 steps a day. These users spent an average between 8 to 13 hours in sedentary, 5 hours in lightly active, and 1 to 2 hour for fairly and very active.
Sleep Vs. Calories Burnt
Do people sleep more burn less calories? Plotting the two variables we can see that there is not much a correlation.
## `geom_smooth()` using formula 'y ~ x'